Posted by twapi 18 hours ago
Also bro: Run /clearbetween tasks. This prevents prior irrelevant context from being sent back to the model, which can reduce token usage. Set your model and effort level before you start. Changing either one mid-conversation can bust your prompt cache, which can increase token cost. @-mention files instead of naming them. The file gets attached to your message directly, which saves a Read call, or a search if Claude has to go find it. Add quiet flags to noisy commands, or run them in a subagent. Command output is added to the conversation just like a file, and stays there for the rest of the session. Run /context once in a fresh session. It shows what's loaded (CLAUDE.md, MCP tool definitions), so you can cut out anything unnecessary. /compact before you take a break from your keyboard. The prompt cache expires after an hour, and summarizing a conversation is much cheaper while it's still cached.
I remember when the internet was an exchange of ideas instead of using gender to justify value of bad ideas
don’t do that, it is weird, use “bruh” or “dude”
Oh yes, Claude will do all sorts of different things -- it depends on how you use it! You should totally learn all of these little finicky things ... because now completing your tasks cost money. It's not "free" anymore haha like when you used your old text editor, what are you a grandpa?
Oh, and those things will definitely change, as we (the priests of Claude) are vibe coding the system you use to do your little "tasks" ... right, you can't see how it works ... the code is not available. It's all good, just trust us -- we're totally looking out for you.
I mean it is utterly ridiculous to talk around this model of development. There are so many walls between you and doing the thing you want to do.
Agents are great, but the notion of "best tricks" for how to best use an opaque costful tool which will, by all odds, be completely different in a few months time is quite funny.
You know what won't change? A fucking text editor. Or your pi config, or a local model you run and trust.
Why do you think that Anthropic wants fewer tokens inputted and outputted?
They have also been supply constrained on compute and if users cost them less in compute they can more subscriptions and less customer frustration.
I agree they want you to have a subscription. That doesn't mean they aren't aligned with their subscribers.
And the unit economics need to be there because there are competitors in the space. They can't just skin you on tokens or you'll jump ship.
seriously... priorities yeah?
Everything is version pinned and a deliberate choice to change, and a git revert away from changing back.
TBF the models may change underneath me to some extent still, but the cost benefit of running them myself doesn't pan out yet (for agentic coding at least, don't have enough local vram to get a usable context window and generation speed, self hosting on runpod or similar isn't economically sensible for my current consumption though I have tinkered with it)
It's wildly lazy.
Am I to believe the creators, knowing full well that the source will, as Boris Cherny put it in a recent interview, be deleted and rewritten from scratch at the release of the next big model?
Further: I'm responding to content in the blog post itself:
> Until pretty recently, the tools you wrote code with were a flat fee (or free). Your editor cost the same whether you fixed one test or fifty that afternoon, so an individual task didn't really have a price of its own.
I find this type of prose ridiculous. It conveys "this is the way things are now, get used to it".
Does that make sense?
i guess you do? claude code is the commercial closed sourced version provides by ant. reading a mini version of vllm or sglang and then read codex source code or grok build source code will teach you all things taught by this article, fully in the open
it is like saying that you have no insights into some $commercial_db_system which is kinda true but imagine if the article is to teach you indices, query normalization, etc..
This is absolutely what AI companies and AI lovers want you to believe
I mean, agentic coding software is hardly the first tool to exist where learning some idiosyncrasies of how to use it well can result in more efficiency and cost savings.
- I'm happy to learn how to use tools efficiently
- I like to be able to inspect my tools
- I'm against tools changing underneath me
Are you against any of these points?
and as is normal for hosted models, almost everything... based on load flucation they may even send your prompt to a quantised model
I've never become used to it. My impression is that the constant churn has accelerated. Plausible drivers are (1) normalize novelty as desirable (like fast fashion), (2) product developer/designer incentive structures that reward revolutionary change over progressive refinement. The global switch to subscription models and continuous deployment didn't help.
> more like services and less like physical tools that never change.
I'm not sure that constant change is a characteristic feature of services, especially not professional services.
It used to be that you bought a piece of software and used that version until you decided it was worth upgrading, like a particular physical tool. The software still evolved, just like the design of physical tools can, in principle, evolve.
All that said, agentic AI tooling is evolving so rapidly I'm not sure an expectation of stability is realistic.
But Claude is running on someone else's computer, not yours, so it's not Photoshop so much as AWS. Or a rented server farm, if AWS is too new school for you. Of course there's an ongoing cost! And if you configure the server to use more electricity, you get billed more.
If you want to do agentic tooling locally, you can do that—the models aren't quite as good, but they're not bad either. But be warned, for the large models you're going to have to acquire some serious hardware, to the point where you may wish you'd chosen to just rent it instead!
My contention is that we should be building towards less churn, not more. I'm aware that some churn is the cost of engaging in any sort of enterprise, but I'm deeply suspicious of an AI company inserting themselves between me, and the tasks I wish to do with my device -- with a completely opaque system that I can't really "learn".
A postgres index post is unlikely to reach front page. It's already part if the docs, and should include more context to be read worthy.
They are not equal comparison.
This before the fact that there is no guarantee that a model follows your agent instructions (plenty of easy to reach for research on it), and you also get suggestions by devs at these companies to wipe parts of your model's instructions because the model is better now tm.
If cloud providers change their billing quasi monthly, and if you'd need to fiddle with your indexes every couple of days. I'm not sure we'd be using them as much.
There is interesting information about the inference pipeline, but almost too late to the party (by at least a year), and for which audience? Techies understand in broad strokes the tech if they are interested, normies will definitely not read it.
All that to say, that yes, it's worth having a laugh. If for nothing else, as a release valve for all the problems they create in the real non-VC world.
Anthropic is IPOing in October according to news, you might be interested in investing.
But you might be right, engineering around the difficult LLM primitive might be a task which is just too hard for your typical software engineer, as you said, they want predictability, hand holding, determinism, most are unable to deal with the real world which is not a spherical cow in a vacuum. So I guess they can stick to simple very well understood primitives like EC2 or Postgres and leave dealing with LLMs for others.
- https://github.com/anthropics/claude-code/issues/47756 > [BUG] /clear bleeds into the next session (what also breaks cache)
- https://github.com/anthropics/claude-code/issues/47098 > [BUG] new sessions will *never* hit a (full)cache
If you type /resume right after clear, the first thing in the list is the session you just cleared.
* In theory the system prompt is always the same and should therefore be cached, but in practice there's some dynamic strings in there so it doesn't work that way. (Unless they changed this recently.)
With Qwen 3.8 27B, we're one step closer to on-device LLMs that can replace subscriptions.
if youre working on the same codebase, that cache stays quite relevant, and i dont think they make the case that clearing and reading the same couple files over and over again is cheaper that relying on it already being cached. same with doing some of the same teaching claude the right way to approach changes in that codebase again and again.
what would be nice is pulling back and reusing an earlier part of the cache for the later two tasks, but claude code doesnt make that particularly easy, and using an LLM to pick where to go back to isnt really gonna save much when it reads all the same text again.
I know we supposed to do this but is there any particular reason why such things cannot be supported? I thought its running on same model just different settings like reasoning. This would be super useful.
I sometimes just leave some goals or something running before I go to bed or out and I don’t want to pay the cache text when I come back.